Volunteer Summary

Table

Text

sets

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict sets with group and time_point (formula: sets ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.43) and the part related to the fixed effects alone (marginal R2) is of 0.04. The model’s intercept, corresponding to group = control and time_point = 1st, is at 19.04 (95% CI [18.48, 19.59], t(156) = 67.81, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.84, 95% CI [-0.02, 1.70], t(156) = 1.92, p = 0.055; Std. beta = 0.39, 95% CI [-7.85e-03, 0.79])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.30, 95% CI [-1.06, 0.46], t(156) = -0.77, p = 0.440; Std. beta = -0.14, 95% CI [-0.49, 0.21])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.17, 95% CI [-0.90, 1.25], t(156) = 0.32, p = 0.751; Std. beta = 0.08, 95% CI [-0.42, 0.58])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

setv

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict setv with group and time_point (formula: setv ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.57) and the part related to the fixed effects alone (marginal R2) is of 0.01. The model’s intercept, corresponding to group = control and time_point = 1st, is at 11.04 (95% CI [10.60, 11.47], t(156) = 49.87, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.39, 95% CI [-0.29, 1.07], t(156) = 1.13, p = 0.258; Std. beta = 0.23, 95% CI [-0.17, 0.63])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.21, 95% CI [-0.31, 0.73], t(156) = 0.79, p = 0.430; Std. beta = 0.12, 95% CI [-0.18, 0.43])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.12, 95% CI [-0.85, 0.61], t(156) = -0.33, p = 0.742; Std. beta = -0.07, 95% CI [-0.51, 0.36])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

maks

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict maks with group and time_point (formula: maks ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.70) and the part related to the fixed effects alone (marginal R2) is of 0.01. The model’s intercept, corresponding to group = control and time_point = 1st, is at 44.58 (95% CI [43.57, 45.59], t(156) = 86.31, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.87, 95% CI [-0.71, 2.45], t(156) = 1.08, p = 0.279; Std. beta = 0.22, 95% CI [-0.18, 0.63])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.16, 95% CI [-1.19, 0.88], t(156) = -0.30, p = 0.767; Std. beta = -0.04, 95% CI [-0.31, 0.22])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.14, 95% CI [-1.31, 1.58], t(156) = 0.19, p = 0.852; Std. beta = 0.04, 95% CI [-0.34, 0.41])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ibs

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ibs with group and time_point (formula: ibs ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.65) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 15.46 (95% CI [14.90, 16.01], t(156) = 54.44, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.24, 95% CI [-0.62, 1.11], t(156) = 0.55, p = 0.581; Std. beta = 0.11, 95% CI [-0.29, 0.52])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.20, 95% CI [-0.41, 0.81], t(156) = 0.65, p = 0.514; Std. beta = 0.09, 95% CI [-0.19, 0.38])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.32, 95% CI [-0.53, 1.18], t(156) = 0.74, p = 0.459; Std. beta = 0.15, 95% CI [-0.25, 0.55])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ers_e

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ers_e with group and time_point (formula: ers_e ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.65) and the part related to the fixed effects alone (marginal R2) is of 0.03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 12.16 (95% CI [11.78, 12.53], t(156) = 63.82, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.12, 95% CI [-0.46, 0.70], t(156) = 0.39, p = 0.693; Std. beta = 0.08, 95% CI [-0.32, 0.48])
• The effect of time point [2nd] is statistically significant and negative (beta = -0.51, 95% CI [-0.92, -0.10], t(156) = -2.44, p = 0.015; Std. beta = -0.35, 95% CI [-0.64, -0.07])
• The interaction effect of time point [2nd] on group [treatment] is statistically significant and positive (beta = 0.65, 95% CI [0.07, 1.22], t(156) = 2.19, p = 0.028; Std. beta = 0.45, 95% CI [0.05, 0.85])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ers_r

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ers_r with group and time_point (formula: ers_r ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.43) and the part related to the fixed effects alone (marginal R2) is of 0.03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 11.09 (95% CI [10.71, 11.47], t(156) = 57.30, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.39, 95% CI [-0.20, 0.98], t(156) = 1.29, p = 0.199; Std. beta = 0.26, 95% CI [-0.14, 0.67])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.09, 95% CI [-0.61, 0.43], t(156) = -0.32, p = 0.746; Std. beta = -0.06, 95% CI [-0.41, 0.30])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.20, 95% CI [-0.54, 0.93], t(156) = 0.52, p = 0.603; Std. beta = 0.13, 95% CI [-0.37, 0.64])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

pss_pa

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict pss_pa with group and time_point (formula: pss_pa ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.46) and the part related to the fixed effects alone (marginal R2) is of 0.03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 44.53 (95% CI [43.36, 45.69], t(156) = 74.87, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 1.00, 95% CI [-0.82, 2.81], t(156) = 1.08, p = 0.281; Std. beta = 0.22, 95% CI [-0.18, 0.62])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -1.47, 95% CI [-3.03, 0.10], t(156) = -1.84, p = 0.066; Std. beta = -0.32, 95% CI [-0.66, 0.02])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.59, 95% CI [-1.62, 2.80], t(156) = 0.52, p = 0.602; Std. beta = 0.13, 95% CI [-0.36, 0.61])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

pss_ps

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict pss_ps with group and time_point (formula: pss_ps ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.59) and the part related to the fixed effects alone (marginal R2) is of 0.03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 26.46 (95% CI [24.56, 28.35], t(156) = 27.37, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -1.96, 95% CI [-4.91, 0.99], t(156) = -1.30, p = 0.194; Std. beta = -0.26, 95% CI [-0.66, 0.13])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 1.41, 95% CI [-0.85, 3.67], t(156) = 1.22, p = 0.222; Std. beta = 0.19, 95% CI [-0.12, 0.50])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -1.42, 95% CI [-4.60, 1.76], t(156) = -0.88, p = 0.381; Std. beta = -0.19, 95% CI [-0.62, 0.24])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

pss

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict pss with group and time_point (formula: pss ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.61) and the part related to the fixed effects alone (marginal R2) is of 0.03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 44.93 (95% CI [42.11, 47.75], t(156) = 31.26, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -2.95, 95% CI [-7.34, 1.43], t(156) = -1.32, p = 0.187; Std. beta = -0.27, 95% CI [-0.66, 0.13])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 2.85, 95% CI [-0.44, 6.13], t(156) = 1.70, p = 0.090; Std. beta = 0.26, 95% CI [-0.04, 0.56])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -1.96, 95% CI [-6.58, 2.66], t(156) = -0.83, p = 0.405; Std. beta = -0.18, 95% CI [-0.60, 0.24])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki_responsible

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki_responsible with group and time_point (formula: rki_responsible ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.56) and the part related to the fixed effects alone (marginal R2) is of 7.61e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 20.95 (95% CI [19.92, 21.97], t(156) = 40.03, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.75, 95% CI [-0.84, 2.35], t(156) = 0.92, p = 0.356; Std. beta = 0.19, 95% CI [-0.22, 0.60])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.07, 95% CI [-1.31, 1.17], t(156) = -0.11, p = 0.916; Std. beta = -0.02, 95% CI [-0.33, 0.30])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.16, 95% CI [-1.90, 1.59], t(156) = -0.17, p = 0.861; Std. beta = -0.04, 95% CI [-0.49, 0.41])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki_nonlinear

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki_nonlinear with group and time_point (formula: rki_nonlinear ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.57) and the part related to the fixed effects alone (marginal R2) is of 0.01. The model’s intercept, corresponding to group = control and time_point = 1st, is at 13.19 (95% CI [12.44, 13.95], t(156) = 34.24, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.48, 95% CI [-0.69, 1.66], t(156) = 0.80, p = 0.422; Std. beta = 0.17, 95% CI [-0.24, 0.57])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.28, 95% CI [-1.18, 0.63], t(156) = -0.60, p = 0.548; Std. beta = -0.10, 95% CI [-0.41, 0.22])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.46, 95% CI [-0.81, 1.73], t(156) = 0.71, p = 0.477; Std. beta = 0.16, 95% CI [-0.28, 0.60])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki_peer

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki_peer with group and time_point (formula: rki_peer ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.51) and the part related to the fixed effects alone (marginal R2) is of 2.08e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 20.49 (95% CI [19.91, 21.07], t(156) = 69.57, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -0.12, 95% CI [-1.02, 0.78], t(156) = -0.25, p = 0.800; Std. beta = -0.05, 95% CI [-0.46, 0.35])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.09, 95% CI [-0.64, 0.82], t(156) = 0.25, p = 0.801; Std. beta = 0.04, 95% CI [-0.29, 0.37])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.19, 95% CI [-0.84, 1.22], t(156) = 0.36, p = 0.719; Std. beta = 0.09, 95% CI [-0.38, 0.55])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki_expect

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki_expect with group and time_point (formula: rki_expect ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.33) and the part related to the fixed effects alone (marginal R2) is of 0.05. The model’s intercept, corresponding to group = control and time_point = 1st, is at 4.58 (95% CI [4.32, 4.84], t(156) = 34.34, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.35, 95% CI [-0.06, 0.75], t(156) = 1.67, p = 0.096; Std. beta = 0.34, 95% CI [-0.06, 0.74])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.02, 95% CI [-0.37, 0.40], t(156) = 0.08, p = 0.933; Std. beta = 0.02, 95% CI [-0.36, 0.39])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.18, 95% CI [-0.37, 0.73], t(156) = 0.63, p = 0.528; Std. beta = 0.17, 95% CI [-0.37, 0.71])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki with group and time_point (formula: rki ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.57) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 59.21 (95% CI [57.67, 60.75], t(156) = 75.41, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 1.46, 95% CI [-0.93, 3.86], t(156) = 1.20, p = 0.231; Std. beta = 0.25, 95% CI [-0.16, 0.66])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.19, 95% CI [-2.04, 1.66], t(156) = -0.20, p = 0.842; Std. beta = -0.03, 95% CI [-0.35, 0.28])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.65, 95% CI [-1.95, 3.25], t(156) = 0.49, p = 0.623; Std. beta = 0.11, 95% CI [-0.33, 0.56])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

raq_possible

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict raq_possible with group and time_point (formula: raq_possible ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.52) and the part related to the fixed effects alone (marginal R2) is of 0.01. The model’s intercept, corresponding to group = control and time_point = 1st, is at 15.68 (95% CI [15.22, 16.14], t(156) = 66.86, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -0.16, 95% CI [-0.88, 0.56], t(156) = -0.44, p = 0.663; Std. beta = -0.09, 95% CI [-0.49, 0.31])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.30, 95% CI [-0.88, 0.28], t(156) = -1.02, p = 0.306; Std. beta = -0.17, 95% CI [-0.50, 0.16])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.79, 95% CI [-0.03, 1.61], t(156) = 1.89, p = 0.059; Std. beta = 0.44, 95% CI [-0.02, 0.91])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

raq_difficulty

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict raq_difficulty with group and time_point (formula: raq_difficulty ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.53) and the part related to the fixed effects alone (marginal R2) is of 9.29e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 12.53 (95% CI [12.16, 12.89], t(156) = 67.69, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -0.35, 95% CI [-0.92, 0.21], t(156) = -1.22, p = 0.223; Std. beta = -0.25, 95% CI [-0.65, 0.15])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.11, 95% CI [-0.56, 0.34], t(156) = -0.46, p = 0.642; Std. beta = -0.08, 95% CI [-0.40, 0.25])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.34, 95% CI [-0.29, 0.98], t(156) = 1.06, p = 0.290; Std. beta = 0.24, 95% CI [-0.21, 0.70])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

raq

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict raq with group and time_point (formula: raq ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.58) and the part related to the fixed effects alone (marginal R2) is of 8.90e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 28.21 (95% CI [27.46, 28.97], t(156) = 73.27, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -0.51, 95% CI [-1.69, 0.66], t(156) = -0.85, p = 0.395; Std. beta = -0.18, 95% CI [-0.58, 0.23])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.36, 95% CI [-1.25, 0.54], t(156) = -0.78, p = 0.434; Std. beta = -0.12, 95% CI [-0.43, 0.18])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 1.08, 95% CI [-0.18, 2.33], t(156) = 1.68, p = 0.093; Std. beta = 0.37, 95% CI [-0.06, 0.80])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

who

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict who with group and time_point (formula: who ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.67) and the part related to the fixed effects alone (marginal R2) is of 8.70e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 14.60 (95% CI [13.47, 15.73], t(156) = 25.29, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.43, 95% CI [-1.33, 2.19], t(156) = 0.48, p = 0.634; Std. beta = 0.10, 95% CI [-0.31, 0.51])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.13, 95% CI [-1.34, 1.07], t(156) = -0.22, p = 0.828; Std. beta = -0.03, 95% CI [-0.31, 0.25])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.67, 95% CI [-1.02, 2.37], t(156) = 0.78, p = 0.434; Std. beta = 0.16, 95% CI [-0.24, 0.55])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

phq

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict phq with group and time_point (formula: phq ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.81) and the part related to the fixed effects alone (marginal R2) is of 1.22e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 3.67 (95% CI [2.72, 4.61], t(156) = 7.60, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -0.22, 95% CI [-1.69, 1.26], t(156) = -0.29, p = 0.773; Std. beta = -0.06, 95% CI [-0.47, 0.35])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.13, 95% CI [-0.65, 0.91], t(156) = 0.32, p = 0.748; Std. beta = 0.04, 95% CI [-0.18, 0.25])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.07, 95% CI [-1.15, 1.02], t(156) = -0.12, p = 0.902; Std. beta = -0.02, 95% CI [-0.32, 0.28])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

gad

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict gad with group and time_point (formula: gad ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.74) and the part related to the fixed effects alone (marginal R2) is of 6.39e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 3.40 (95% CI [2.45, 4.36], t(156) = 6.99, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -0.58, 95% CI [-2.06, 0.91], t(156) = -0.76, p = 0.445; Std. beta = -0.16, 95% CI [-0.59, 0.26])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.11, 95% CI [-0.79, 1.02], t(156) = 0.25, p = 0.806; Std. beta = 0.03, 95% CI [-0.22, 0.29])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.03, 95% CI [-1.30, 1.23], t(156) = -0.05, p = 0.959; Std. beta = -9.47e-03, 95% CI [-0.37, 0.35])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

nb_pcs

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict nb_pcs with group and time_point (formula: nb_pcs ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.73) and the part related to the fixed effects alone (marginal R2) is of 7.85e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 51.86 (95% CI [49.97, 53.74], t(156) = 53.85, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -1.66, 95% CI [-4.60, 1.28], t(156) = -1.10, p = 0.269; Std. beta = -0.23, 95% CI [-0.63, 0.17])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.98, 95% CI [-2.80, 0.84], t(156) = -1.06, p = 0.291; Std. beta = -0.13, 95% CI [-0.38, 0.11])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 2.05, 95% CI [-0.50, 4.60], t(156) = 1.58, p = 0.115; Std. beta = 0.28, 95% CI [-0.07, 0.63])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

nb_mcs

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict nb_mcs with group and time_point (formula: nb_mcs ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.60) and the part related to the fixed effects alone (marginal R2) is of 7.70e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 50.01 (95% CI [47.85, 52.18], t(156) = 45.31, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 1.47, 95% CI [-1.90, 4.84], t(156) = 0.86, p = 0.392; Std. beta = 0.18, 95% CI [-0.23, 0.59])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.03, 95% CI [-2.49, 2.55], t(156) = 0.02, p = 0.983; Std. beta = 3.30e-03, 95% CI [-0.30, 0.31])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -9.95e-03, 95% CI [-3.55, 3.53], t(156) = -5.51e-03, p = 0.996; Std. beta = -1.21e-03, 95% CI [-0.43, 0.43])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

Table